ArticleNature communications2023
Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed, 94 citations in OpenAlex.
- ProFormer: generalizable classification of single-cell and plasma proteomes using deep learning.Nature communications · 2026Article
- Multiomics analysis reveals dermokine as a regulator of keratinocyte differentiation and adhesion.JCI insight · 2026Article
- Addressing multiple facets of ligand-receptor network inference including single-cell proteomics.Nucleic acids research · 2026Article
- Dissecting autonomous enzymatic variability in single cells.Nature communications · 2026Article
- EasySCP unveils extensive liver zonation at single-cell proteomics resolution.Nature communications · 2026Article
- Pro-regenerative fingerprints identified in a sub-population of adult mouse cardiomyocytes by integrative single-cell proteomics.Genome biology · 2026Article
- omicsGMF: a multi-tool for dimensionality reduction, batch correction and imputation in bulk- and single-cell proteomics.Nature communications · 2026Article
- What Are the Practical Applications of Single-Cell Proteomics?Proteomes · 2026Article
- Single-Cell Proteomic Technologies: Tools in the Quest for Principles.Annual review of biophysics · 2026Review
- Artificial intelligence-enabled multi-scale virtual cell: perspective, challenges, and opportunities.Briefings in bioinformatics · 2026Review
- Resolving Single-Cell Gene Expression by Pseudotemporal Integration of Transcriptomic and Proteomic Datasets.Molecular & cellular proteomics : MCP · 2026Article
- Single cell proteomic analysis defines discrete neutrophil functional states in human glioblastoma.Nature communications · 2025Article
- ERBB2 signaling drives immune cell evasion and resistance against immunotherapy in small cell lung cancer.Nature communications · 2025Article
- The pursuit of ultrasensitive phosphoproteomics to unravel signalling in rare cells.Communications biology · 2025Review
- Review
- Benchmarking informatics workflows for data-independent acquisition single-cell proteomics.Nature communications · 2025Article
- High-Throughput Label-free Single-Cell Proteomics Enabled by Multicolumn NanoLC with a 5-min Cycle Time.Research square · 2025Article
- Proteomic Insight Into Alzheimer's Disease Pathogenesis Pathways.Proteomics · 2025Review
- Single-cell proteomics using mass spectrometry.Cell genomics · 2025Review
- Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples.Analytical chemistry · 2025Article
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.